Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Active power limit source has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Power factor set point has constant value "0" Constant
Power factor set point source has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Reactive power generator 0,Total accumulated [var] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Total reactive power [var] has constant value "0" Constant
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°]High correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W]High correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
Grid Production ReactivePower Min. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V]High correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V]High correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Blades PitchAngle Min. [°] and 6 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average ServiceOn Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h] and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Active Power Gen 2 Avg. [W] is highly overall correlated with HourCounters Average Gen2 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 3 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 1 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (58.9%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (53.3%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (53.2%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (54.6%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (61.7%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (76.6%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (78.0%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (76.5%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (73.2%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (76.7%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (62.1%) Imbalance
Gear Oil TemperatureLevel1 Avg. [°C] is highly imbalanced (68.6%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (74.3%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (69.2%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (64.5%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (56.5%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (63.5%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (51.0%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (56.2%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.9%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (85.9%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.3%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (68.4%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (80.1%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (83.5%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (67.0%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (61.1%) Imbalance
Grid RotorInvPhase3 Temp. Avg. [°C] is highly imbalanced (56.1%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (76.9%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (66.5%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.5%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (90.9%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (91.2%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (90.7%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (74.7%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (74.2%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (74.3%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (72.5%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (71.6%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (55.1%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (74.9%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (57.1%) Imbalance
Grid Production ReactivePower Max. [W] is highly imbalanced (51.2%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (81.4%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (78.1%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (76.7%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (78.8%) Imbalance
Active power limit [W] is highly imbalanced (99.6%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (82.4%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (54.3%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (73.6%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (65.3%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (75.4%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (68.9%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (55.8%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (54.5%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (56.0%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (73.8%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (79.2%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (72.5%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (58.8%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.8%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (99.2%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (99.1%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (96.8%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (80.4%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (60.2%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (99.6%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (97.0%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (66.1%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (96.8%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (67.7%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (84.6%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (73.2%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (78.0%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (66.2%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (55.7%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (57.5%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.9%) Imbalance
Total Active power [W] is highly imbalanced (94.7%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-14 17:27:35.204325
Analysis finished2025-05-14 17:28:02.865464
Duration27.66 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-14T19:28:02.906232image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T19:28:02.988079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24048 
1
 
2160

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Length

2025-05-14T19:28:03.062238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.098398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Most occurring characters

ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24048
91.8%
1 2160
 
8.2%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23604 
1
2604 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Length

2025-05-14T19:28:03.143413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.318328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23604
90.1%
1 2604
 
9.9%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23596 
1
2612 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Length

2025-05-14T19:28:03.362264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.398020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Most occurring characters

ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23596
90.0%
1 2612
 
10.0%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23707 
1
2501 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Length

2025-05-14T19:28:03.442944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.478783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Most occurring characters

ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23707
90.5%
1 2501
 
9.5%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24251 
1
 
1957

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Length

2025-05-14T19:28:03.523714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.560251image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24251
92.5%
1 1957
 
7.5%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25206 
1
 
1002

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Length

2025-05-14T19:28:03.604672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.644132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25206
96.2%
1 1002
 
3.8%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25283 
1
 
925

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Length

2025-05-14T19:28:03.690879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.729129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25203 
1
 
1005

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%

Length

2025-05-14T19:28:03.776563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.813366image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25203
96.2%
1 1005
 
3.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22554 
1
3654 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%

Length

2025-05-14T19:28:03.857254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.897175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%

Most occurring characters

ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22554
86.1%
1 3654
 
13.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25007 
1
 
1201

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%

Length

2025-05-14T19:28:03.943247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:03.980255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25007
95.4%
1 1201
 
4.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21448 
1
4760 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Length

2025-05-14T19:28:04.025725image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.062845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Most occurring characters

ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21448
81.8%
1 4760
 
18.2%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25212 
1
 
996

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Length

2025-05-14T19:28:04.109931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.146771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25212
96.2%
1 996
 
3.8%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:04.189926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.223691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:04.265666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.299065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24280 
1
 
1928

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%

Length

2025-05-14T19:28:04.340111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.375435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%

Most occurring characters

ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24280
92.6%
1 1928
 
7.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24722 
1
 
1486

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%

Length

2025-05-14T19:28:04.417098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.452917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24722
94.3%
1 1486
 
5.7%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:04.496981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.530180image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25074 
1
 
1134

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%

Length

2025-05-14T19:28:04.571211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.607889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25074
95.7%
1 1134
 
4.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24760 
1
 
1448

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%

Length

2025-05-14T19:28:04.650635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.686039image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24760
94.5%
1 1448
 
5.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24448 
1
 
1760

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%

Length

2025-05-14T19:28:04.730271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.766022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%

Most occurring characters

ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24448
93.3%
1 1760
 
6.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23862 
1
 
2346

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Length

2025-05-14T19:28:04.809678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.846162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23862
91.0%
1 2346
 
9.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24382 
1
 
1826

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Length

2025-05-14T19:28:04.890288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:04.926009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring characters

ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24382
93.0%
1 1826
 
7.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23120 
1
3088 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Length

2025-05-14T19:28:04.970710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.007120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23120
88.2%
1 3088
 
11.8%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23413 
1
2795 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Length

2025-05-14T19:28:05.052824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.090779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Most occurring characters

ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23413
89.3%
1 2795
 
10.7%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22735 
1
3473 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Length

2025-05-14T19:28:05.134788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.170618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring characters

ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23835 
1
 
2373

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Length

2025-05-14T19:28:05.216875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.253114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23835
90.9%
1 2373
 
9.1%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22927 
1
3281 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Length

2025-05-14T19:28:05.298321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.334935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22927
87.5%
1 3281
 
12.5%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25906 
1
 
302

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Length

2025-05-14T19:28:05.379009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.414062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25906
98.8%
1 302
 
1.2%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25686 
1
 
522

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Length

2025-05-14T19:28:05.457736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.493161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25686
98.0%
1 522
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25920 
1
 
288

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Length

2025-05-14T19:28:05.536823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.572235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25920
98.9%
1 288
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24713 
1
 
1495

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Length

2025-05-14T19:28:05.614586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.650447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24713
94.3%
1 1495
 
5.7%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25400 
1
 
808

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Length

2025-05-14T19:28:05.694832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.730495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25400
96.9%
1 808
 
3.1%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25569 
1
 
639

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%

Length

2025-05-14T19:28:05.774094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:05.948254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25569
97.6%
1 639
 
2.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22526 
1
3682 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%

Length

2025-05-14T19:28:05.990376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.026356image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%

Most occurring characters

ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22526
86.0%
1 3682
 
14.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:06.071420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.104513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24616 
1
 
1592

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%

Length

2025-05-14T19:28:06.145022image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.180229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%

Most occurring characters

ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24616
93.9%
1 1592
 
6.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24208 
1
 
2000

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%

Length

2025-05-14T19:28:06.222219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.259090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%

Most occurring characters

ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24208
92.4%
1 2000
 
7.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23072 
1
3136 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%

Length

2025-05-14T19:28:06.300933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.337614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%

Most occurring characters

ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23072
88.0%
1 3136
 
12.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23831 
1
 
2377

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Length

2025-05-14T19:28:06.383368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.419255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23831
90.9%
1 2377
 
9.1%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25224 
1
 
984

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Length

2025-05-14T19:28:06.463055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.499904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24582 
1
 
1626

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%

Length

2025-05-14T19:28:06.543204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.580190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24582
93.8%
1 1626
 
6.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26080 
1
 
128

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Length

2025-05-14T19:28:06.624754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.660881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26080
99.5%
1 128
 
0.5%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25905 
1
 
303

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Length

2025-05-14T19:28:06.703394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.740732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25905
98.8%
1 303
 
1.2%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25918 
1
 
290

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Length

2025-05-14T19:28:06.783023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.818442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25918
98.9%
1 290
 
1.1%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25897 
1
 
311

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Length

2025-05-14T19:28:06.863518image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.899186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Most occurring characters

ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25897
98.8%
1 311
 
1.2%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25100 
1
 
1108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Length

2025-05-14T19:28:06.943401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:06.979223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25100
95.8%
1 1108
 
4.2%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25068 
1
 
1140

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Length

2025-05-14T19:28:07.021261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.056485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25068
95.7%
1 1140
 
4.3%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25076 
1
 
1132

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Length

2025-05-14T19:28:07.100020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.135645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Most occurring characters

ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25076
95.7%
1 1132
 
4.3%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24965 
1
 
1243

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Length

2025-05-14T19:28:07.179423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.216883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24965
95.3%
1 1243
 
4.7%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24915 
1
 
1293

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Length

2025-05-14T19:28:07.259565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.297803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Most occurring characters

ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24915
95.1%
1 1293
 
4.9%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23753 
1
2455 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Length

2025-05-14T19:28:07.340666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.378208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Most occurring characters

ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23753
90.6%
1 2455
 
9.4%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25107 
1
 
1101

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Length

2025-05-14T19:28:07.424173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.459607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Most occurring characters

ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25107
95.8%
1 1101
 
4.2%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23910 
1
 
2298

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%

Length

2025-05-14T19:28:07.501552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.539335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%

Most occurring characters

ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23910
91.2%
1 2298
 
8.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23428 
1
2780 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Length

2025-05-14T19:28:07.583711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.619957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23428
89.4%
1 2780
 
10.6%

Grid Production ReactivePower Min. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22628 
1
3580 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Length

2025-05-14T19:28:07.666494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.704499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring characters

ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22628
86.3%
1 3580
 
13.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21192 
1
5016 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Length

2025-05-14T19:28:07.749193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.787418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Most occurring characters

ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21192
80.9%
1 5016
 
19.1%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25466 
1
 
742

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Length

2025-05-14T19:28:07.831783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.867436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25466
97.2%
1 742
 
2.8%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25290 
1
 
918

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Length

2025-05-14T19:28:07.912354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:07.948659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25290
96.5%
1 918
 
3.5%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25215 
1
 
993

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Length

2025-05-14T19:28:07.991387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.028620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25215
96.2%
1 993
 
3.8%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25326 
1
 
882

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Length

2025-05-14T19:28:08.070603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.107183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25326
96.6%
1 882
 
3.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.151141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.184434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.223637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.258756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.298506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.332033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.372775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.406378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.445459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.480140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.519276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.552753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.593513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.772007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.811241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.846080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26201 
1
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Length

2025-05-14T19:28:08.885326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.920863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26201
> 99.9%
1 7
 
< 0.1%

Active power limit source
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:08.964460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:08.997859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:09.037212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.072040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:09.111171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.144347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point source
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:09.185279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.218447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25518 
1
 
690

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Length

2025-05-14T19:28:09.257573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.295084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25518
97.4%
1 690
 
2.6%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23684 
1
2524 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Length

2025-05-14T19:28:09.337948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.381150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23684
90.4%
1 2524
 
9.6%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25032 
1
 
1176

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Length

2025-05-14T19:28:09.427438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.463477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25032
95.5%
1 1176
 
4.5%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24502 
1
 
1706

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%

Length

2025-05-14T19:28:09.505754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.543132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%

Most occurring characters

ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24502
93.5%
1 1706
 
6.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25138 
1
 
1070

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%

Length

2025-05-14T19:28:09.585834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.621304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25138
95.9%
1 1070
 
4.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23224 
1
2984 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Length

2025-05-14T19:28:09.665111image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.702292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Most occurring characters

ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23224
88.6%
1 2984
 
11.4%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24743 
1
 
1465

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Length

2025-05-14T19:28:09.747058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.784543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24743
94.4%
1 1465
 
5.6%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:09.827074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.860318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23803 
1
2405 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Length

2025-05-14T19:28:09.901193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:09.937715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring characters

ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23702 
1
2506 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Length

2025-05-14T19:28:09.981824image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.019851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23702
90.4%
1 2506
 
9.6%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23818 
1
2390 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Length

2025-05-14T19:28:10.064083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.100121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Most occurring characters

ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23818
90.9%
1 2390
 
9.1%

Blades PitchAngle StdDev [°]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23067 
1
3141 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

Length

2025-05-14T19:28:10.145902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.181980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

Most occurring characters

ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23067
88.0%
1 3141
 
12.0%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25047 
1
 
1161

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

Length

2025-05-14T19:28:10.226109image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.263275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25047
95.6%
1 1161
 
4.4%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25352 
1
 
856

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

Length

2025-05-14T19:28:10.305532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.341202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

Most occurring characters

ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25352
96.7%
1 856
 
3.3%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24969 
1
 
1239

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

Length

2025-05-14T19:28:10.385021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.420381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

Most occurring characters

ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24969
95.3%
1 1239
 
4.7%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24040 
1
 
2168

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%

Length

2025-05-14T19:28:10.462476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.500027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%

Most occurring characters

ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24040
91.7%
1 2168
 
8.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:10.543844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.577128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26204 
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Length

2025-05-14T19:28:10.617856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.653426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26204
> 99.9%
1 4
 
< 0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26190 
1
 
18

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

Length

2025-05-14T19:28:10.695667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.733813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26190
99.9%
1 18
 
0.1%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26189 
1
 
19

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Length

2025-05-14T19:28:10.776259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.812248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26189
99.9%
1 19
 
0.1%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26120 
1
 
88

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

Length

2025-05-14T19:28:10.856391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.891846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26120
99.7%
1 88
 
0.3%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25412 
1
 
796

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Length

2025-05-14T19:28:10.934059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:10.971043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring characters

ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25412
97.0%
1 796
 
3.0%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24142 
1
 
2066

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%

Length

2025-05-14T19:28:11.013541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.049114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%

Most occurring characters

ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24142
92.1%
1 2066
 
7.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23265 
1
2943 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Length

2025-05-14T19:28:11.092916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.129309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring characters

ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23265
88.8%
1 2943
 
11.2%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26200 
1
 
8

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Length

2025-05-14T19:28:11.173344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.210510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26200
> 99.9%
1 8
 
< 0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26127 
1
 
81

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%

Length

2025-05-14T19:28:11.252805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.288231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26127
99.7%
1 81
 
0.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24561 
1
 
1647

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Length

2025-05-14T19:28:11.332113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.367689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24561
93.7%
1 1647
 
6.3%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26122 
1
 
86

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Length

2025-05-14T19:28:11.410024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.447112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26122
99.7%
1 86
 
0.3%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:11.489434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.522477image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:11.563929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.597553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:11.636847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.817108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:11.856633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.889834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:11.930506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:11.963528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.002928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.038082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.077037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.110303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.151004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.184847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.224104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.259040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.298208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.331706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:12.373036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.406182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24668 
1
 
1540

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Length

2025-05-14T19:28:12.444995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.482100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring characters

ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24668
94.1%
1 1540
 
5.9%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25625 
1
 
583

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Length

2025-05-14T19:28:12.524112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.559617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25625
97.8%
1 583
 
2.2%

Production LatestAverage Active Power Gen 2 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25012 
1
 
1196

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Length

2025-05-14T19:28:12.604291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.639691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25012
95.4%
1 1196
 
4.6%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25285 
1
 
923

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Length

2025-05-14T19:28:12.681672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.719977image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25285
96.5%
1 923
 
3.5%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24562 
1
 
1646

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Length

2025-05-14T19:28:12.763125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.798847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring characters

ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24562
93.7%
1 1646
 
6.3%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23796 
1
2412 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Length

2025-05-14T19:28:12.842915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.879184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Most occurring characters

ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23796
90.8%
1 2412
 
9.2%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23940 
1
 
2268

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Length

2025-05-14T19:28:12.923171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:12.961026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring characters

ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23940
91.3%
1 2268
 
8.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
21920 
1
4288 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%

Length

2025-05-14T19:28:13.005365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.041757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%

Most occurring characters

ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 21920
83.6%
1 4288
 
16.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.087697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.121008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.160205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.195052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26207 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Length

2025-05-14T19:28:13.234212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.269622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Total Active power [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26052 
1
 
156

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%

Length

2025-05-14T19:28:13.313458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.349376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26052
99.4%
1 156
 
0.6%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.391471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.426051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.465201image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.498315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.538790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.572199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:28:13.611357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:28:13.645976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Correlations

2025-05-14T19:28:13.763644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Ambient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total Active power [W]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
Active power limit [W]0.0001.0000.0000.0190.0000.0000.0000.0000.0000.0030.0220.0000.0000.0180.0120.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0260.0000.0000.0000.0000.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.000
Ambient Temp. Avg. [°C]0.0000.0001.0000.0040.0170.0000.0060.0060.0040.0000.0040.0000.0000.0000.0230.0270.0060.0130.0070.0250.0230.0100.0210.0050.0260.0000.0260.0000.0110.0160.0140.0110.0300.0240.0060.0210.1100.0390.0000.0000.0110.0110.0050.0000.0000.0000.0080.0000.0000.0000.0070.0000.0000.0070.0000.0000.0000.0030.0000.0170.0000.0000.0540.0380.0200.0330.0060.0000.0000.0020.0240.0000.0080.0000.0190.0000.0000.0110.1140.0000.0000.0090.0000.0000.0000.0000.0000.0200.0220.0060.0200.0570.001
Ambient WindDir Absolute Avg. [°]0.0000.0190.0041.0000.1070.0110.0130.0000.0150.0270.0240.0040.0090.0000.0190.0120.0090.0090.0040.0210.0000.0040.0000.0000.0000.0260.0090.0000.0000.0000.0000.0000.0310.0430.0180.0340.0000.0110.0000.0220.0140.0170.0220.0000.0000.0000.0000.0030.0000.0100.0000.0000.0350.0360.0000.0000.0000.0000.0000.0000.0120.0000.0140.0110.0000.0150.0000.0000.0000.0290.0000.0000.0000.0000.0000.0020.0120.0000.0090.0360.0000.0010.0440.0140.0120.0000.0130.0350.0330.0110.0360.0010.000
Ambient WindDir Relative Avg. [°]0.0000.0000.0170.1071.0000.0410.0110.0100.0180.0970.1340.0560.0410.0000.0440.0000.0100.0000.0020.0060.0040.0110.0260.0400.0000.0960.0050.0000.0000.0070.0120.0060.0860.1360.0760.0680.0030.0050.0000.0690.0000.0000.0000.0000.0140.0000.0000.0130.0030.0000.0090.0180.0930.1120.0340.0150.0050.0000.0000.0000.0000.0000.0000.0000.0000.0040.0410.0390.0000.0920.0000.0000.0410.0000.0000.0150.0050.0000.0060.1280.0030.0060.1300.0240.0390.0070.0480.0890.1110.0610.0640.0200.012
Ambient WindSpeed Avg. [m/s]0.0000.0000.0000.0110.0411.0000.1310.1040.0260.1160.0540.0630.0410.0000.0000.0000.0090.0000.0000.0500.0570.0650.0690.0800.0560.0230.0000.0000.0070.0330.0320.0270.1240.0830.0800.0710.0170.0030.0250.0410.1910.1850.1890.0000.2130.0880.0950.0600.2090.0840.0810.0510.0460.0370.0380.0510.0010.0000.0080.0360.0180.0290.0060.0000.0000.0100.0000.0000.0290.0610.0000.0000.0000.0000.0000.0220.0070.0000.0190.0550.1020.0930.0530.0000.0080.2050.0290.1100.0730.0690.0600.0000.000
Ambient WindSpeed Max. [m/s]0.0000.0000.0060.0130.0110.1311.0000.0290.0870.0580.0490.0460.0420.0000.0000.0100.0110.0000.0000.0340.0330.0410.0220.0260.0200.0030.0070.0010.0050.0040.0070.0110.0650.0720.0540.0440.0110.0000.0010.0350.1170.1210.1110.0000.1230.1220.0620.0920.1170.1150.0680.0960.0440.0520.0260.0330.0000.0000.0000.0310.0050.0160.0080.0130.0100.0000.0000.0000.0270.0480.0000.0000.0000.0000.0000.0460.0210.0000.0000.0370.0520.0640.0430.0160.0100.1120.0350.0480.0660.0380.0420.0000.011
Ambient WindSpeed Min. [m/s]0.0000.0000.0060.0000.0100.1040.0291.0000.0160.1000.0180.1320.0930.0080.0090.0000.0000.0000.0090.0260.0070.0330.0270.0310.0000.0000.0000.0000.0040.0100.0210.0000.0710.0470.1010.0530.0110.0000.0000.0640.0790.0830.0830.0050.0720.0430.1070.0590.0770.0510.1130.0600.0940.0170.0800.0690.0020.0060.0000.0100.0000.0050.0000.0000.0030.0000.0000.0000.0550.0680.0000.0000.0000.0000.0000.0560.0080.0100.0000.0510.0490.0740.0500.0220.0600.0780.0670.0700.0360.0850.0470.0000.010
Ambient WindSpeed StdDev [m/s]0.0000.0000.0040.0150.0180.0260.0870.0161.0000.0420.0060.0350.0740.0000.0040.0270.0030.0000.0000.0180.0000.0370.0000.0000.0000.0000.0000.0000.0000.0240.0220.0100.0380.0520.0240.0860.0110.0040.0220.0230.0400.0450.0470.0070.0280.0320.0300.1160.0360.0330.0380.1120.0320.0370.0380.0180.0040.0000.0000.0190.0000.0130.0090.0090.0120.0070.0000.0000.0050.0220.0000.0000.0000.0000.0000.0070.0540.0160.0010.0240.0000.0340.0250.0160.0240.0350.0000.0250.0420.0160.0660.0000.008
Blades PitchAngle Avg. [°]0.0000.0030.0000.0270.0970.1160.0580.1000.0421.0000.2570.4680.4790.0000.0220.0100.0100.0170.0170.0110.0610.0190.1250.1710.0120.0620.0000.0000.0040.0120.0090.0000.2650.2360.2850.2500.0570.0000.0240.2490.1540.1560.1730.0000.2060.2090.2400.2650.2070.1980.1890.2500.4410.1970.2490.2380.0000.0050.0040.0340.0300.0320.0000.0150.0230.0200.1450.1310.1490.4380.0000.0000.1450.0000.0380.0630.0870.0000.0260.4130.0660.2680.3890.0950.2550.2160.3190.2820.2110.2270.2110.0130.071
Blades PitchAngle Max. [°]0.0000.0220.0040.0240.1340.0540.0490.0180.0060.2571.0000.1370.0970.0000.0140.0190.0180.0230.0000.0240.0340.0000.0650.0460.0160.1170.0000.0000.0120.0050.0000.0000.1170.2830.0860.0750.0190.0000.0100.2030.1020.1010.1120.0000.1540.1780.1320.1880.1360.1650.0870.1430.1650.2940.0700.0550.0000.0160.0060.0000.0120.0020.0030.0000.0000.0000.0590.0550.0320.2050.0000.0000.0580.0000.0000.1540.0260.0090.0140.2600.0190.1190.2430.0350.0670.1420.1080.1170.2380.0710.0850.0210.087
Blades PitchAngle Min. [°]0.0000.0000.0000.0040.0560.0630.0460.1320.0350.4680.1371.0000.5540.0000.0340.0070.0050.0000.0000.0200.0780.0080.1120.1360.0210.0170.0000.0060.0070.0130.0080.0090.2520.1620.3760.2470.0430.0130.0110.3240.1310.1380.1510.0120.1690.1520.2030.1980.1830.1540.1720.2100.6730.1180.4690.3870.0000.0080.0000.0260.0360.0290.0090.0200.0290.0250.1140.1020.2830.5700.0000.0000.1150.0000.0380.1060.0520.0000.0070.4770.1600.2930.4510.1660.4480.1960.4650.2600.1420.3060.2110.0200.053
Blades PitchAngle StdDev [°]0.0000.0000.0000.0090.0410.0410.0420.0930.0740.4790.0970.5541.0000.0000.0250.0060.0000.0100.0000.0000.0450.0000.0650.1000.0000.0220.0000.0100.0000.0000.0000.0000.1800.1510.2660.4010.0410.0080.0130.2710.1050.1100.1230.0000.1750.1720.2890.2320.1630.1540.2110.2470.4940.0960.3330.3510.0000.0090.0000.0150.0270.0260.0000.0260.0300.0360.0910.0820.2220.4420.0080.0000.0910.0080.0260.0570.1050.0000.0170.3480.1270.2720.3340.1350.4880.1710.3310.1930.1270.2040.3340.0060.065
Controller Ground Temp. Avg. [°C]0.0000.0180.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0001.0000.0000.0060.0050.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0100.0000.0190.0120.0000.0060.0000.0050.0000.0000.0220.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0150.0000.0050.0050.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0160.0120.0000.0000.0000.0000.0050.0000.0000.0070.0110.0010.0010.0000.0150.000
Controller Hub Temp. Avg. [°C]0.0000.0120.0230.0190.0440.0000.0000.0090.0040.0220.0140.0340.0250.0001.0000.0530.0110.0180.0070.0090.0000.0000.0000.0050.0130.0310.0000.0000.0000.0000.0090.0000.0320.0440.0330.0460.0090.0430.0000.0330.0300.0360.0240.0000.0150.0000.0170.0130.0280.0230.0190.0180.0320.0240.0150.0110.0000.0000.0000.0030.0030.0130.0000.0210.0110.0360.0240.0220.0290.0470.0000.0000.0270.0000.0000.0000.0000.0000.0180.0420.0070.0340.0430.0160.0180.0310.0090.0300.0320.0220.0350.0890.009
Controller Top Temp. Avg. [°C]0.0000.0000.0270.0120.0000.0000.0100.0000.0270.0100.0190.0070.0060.0060.0531.0000.0030.0030.0140.0000.0030.0040.0040.0000.0000.0140.0630.0160.0390.0060.0160.0170.0100.0110.0050.0050.0090.1300.0050.0130.0000.0060.0030.0000.0050.0030.0100.0000.0000.0000.0100.0000.0180.0000.0240.0030.0000.0000.0000.0000.0060.0000.0080.0430.0500.0780.0000.0000.0050.0180.0000.0000.0000.0000.0000.0190.0200.0090.1150.0140.0000.0000.0160.0270.0000.0000.0070.0130.0000.0110.0000.0360.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0060.0090.0100.0090.0110.0000.0030.0100.0180.0050.0000.0050.0110.0031.0000.0000.0000.0160.0280.0100.0110.0060.0370.0280.0270.0000.0220.0450.0490.0500.0140.0110.0030.0220.0220.0140.0240.0310.0200.0240.0220.0000.0100.0120.0140.0000.0170.0170.0100.0040.0130.0250.0000.0220.0000.0000.0000.0380.0120.0210.0210.0280.0080.0230.0000.0010.0230.0060.0000.0000.0000.0000.0000.0000.0000.0040.0150.0330.0170.0000.0330.0050.0180.0120.0090.0130.0060.0000.0290.0000.011
Controller VCP Temp. Avg. [°C]0.0000.0080.0130.0090.0000.0000.0000.0000.0000.0170.0230.0000.0100.0000.0180.0030.0001.0000.0130.0140.0280.0190.0160.0150.0110.0350.0340.0120.0120.0000.0070.0080.0150.0260.0000.0140.0300.0170.0000.0090.0190.0240.0280.0030.0250.0400.0210.0220.0250.0380.0260.0200.0000.0190.0000.0130.0000.0060.0030.0000.0060.0000.0370.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0180.0050.0000.0160.0520.0040.0000.0210.0060.0130.0000.0260.0140.0080.0190.0000.0290.0110.024
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0070.0040.0020.0000.0000.0090.0000.0170.0000.0000.0000.0000.0070.0140.0000.0131.0000.0140.0030.0080.0190.0060.0290.0120.0200.0120.2400.0350.0410.0320.0090.0000.0100.0000.0130.0040.1330.0070.0200.0150.0260.0000.0190.0000.0000.0130.0230.0040.0140.0130.0000.0000.0000.0000.0000.0080.0080.1640.2410.2250.0030.0000.0000.0070.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0040.0120.0120.0080.0000.0080.0000.0000.0130.0280.0000.0150.0090.0140.0040.0000.010
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0250.0210.0060.0500.0340.0260.0180.0110.0240.0200.0000.0000.0090.0000.0160.0140.0141.0000.1970.1890.2060.0850.1760.0000.0240.0130.0210.1100.1170.1190.0930.0310.0400.0290.0360.0130.0420.0260.0390.0420.0390.0050.0650.0650.0250.0350.0530.0510.0070.0300.0030.0080.0080.0000.0070.0000.0000.0580.0340.0580.0100.0030.0000.0000.0050.0000.0180.0000.0000.0000.0040.0000.0000.0220.0120.0300.0180.0200.0350.0000.0130.0000.0200.0560.0000.0730.0470.0530.0430.0000.001
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0230.0000.0040.0570.0330.0070.0000.0610.0340.0780.0450.0060.0000.0030.0280.0280.0030.1971.0000.0980.2840.2550.2270.0000.0330.0060.0360.1230.1320.1340.1490.0820.1110.0950.0450.0320.0380.0650.0340.0340.0340.0000.0460.0440.0400.0270.0420.0340.0170.0250.0760.0250.0630.0450.0060.0000.0020.0500.0410.0510.0180.0290.0230.0330.0140.0150.0000.0860.0000.0000.0130.0000.0000.0280.0290.0000.0260.1150.0450.0140.1070.0270.0380.0450.0440.1480.0670.1160.1020.0060.000
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0100.0040.0110.0650.0410.0330.0370.0190.0000.0080.0000.0000.0000.0040.0100.0190.0080.1890.0981.0000.1580.0520.1680.0480.0000.0430.0320.0550.0490.0460.1100.0310.0620.0680.0130.0000.0180.0150.0460.0410.0430.0000.0410.0570.0200.0250.0500.0590.0260.0220.0000.0130.0170.0290.0070.0000.0120.0410.0290.0380.0000.0000.0000.0050.0280.0300.0090.0000.0000.0000.0270.0000.0000.0080.0230.0000.0020.0150.0240.0160.0140.0240.0180.0470.0240.1150.0660.0560.0520.0000.000
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0210.0000.0260.0690.0220.0270.0000.1250.0650.1120.0650.0000.0000.0040.0110.0160.0190.2060.2840.1581.0000.3520.2100.0340.0270.0210.0320.0880.0790.0890.1890.0780.1740.1080.0500.0220.0270.0970.0350.0410.0450.0000.0650.0790.0610.0560.0530.0640.0320.0500.1010.0580.0750.0900.0040.0000.0000.0180.0370.0290.0000.0190.0040.0190.0210.0200.0000.1140.0000.0000.0210.0050.0020.0000.0150.0150.0130.1370.0470.0000.1320.0000.0420.0560.0910.1920.0840.1470.0980.0050.011
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0000.0050.0000.0400.0800.0260.0310.0000.1710.0460.1360.1000.0000.0050.0000.0060.0150.0060.0850.2550.0520.3521.0000.1300.0370.0220.0230.0190.0630.0660.0600.2060.1200.1810.1090.0370.0100.0140.0950.0270.0280.0310.0000.0570.0650.0730.0530.0440.0460.0290.0470.1380.0620.0860.1200.0030.0000.0000.0260.0260.0200.0000.0100.0000.0160.0270.0190.0300.1610.0000.0000.0260.0000.0000.0040.0240.0000.0060.1660.0290.0360.1580.0310.0690.0450.1270.2240.1090.1530.0970.0150.000
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0260.0000.0000.0560.0200.0000.0000.0120.0160.0210.0000.0000.0130.0000.0370.0110.0290.1760.2270.1680.2100.1301.0000.0210.0270.0120.0500.1490.1340.1460.1080.0350.0380.0470.0310.0070.0200.0110.0200.0180.0210.0000.0300.0350.0070.0170.0250.0260.0090.0130.0000.0000.0160.0130.0060.0000.0140.0550.0350.0530.0000.0100.0000.0090.0000.0000.0170.0060.0000.0000.0000.0000.0000.0010.0080.0000.0000.0230.0100.0000.0200.0000.0120.0280.0080.1020.0520.0540.0450.0000.007
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0000.0000.0260.0960.0230.0030.0000.0000.0620.1170.0170.0220.0000.0310.0140.0280.0350.0120.0000.0000.0480.0340.0370.0211.0000.0070.0000.0000.0000.0080.0000.0560.1370.0370.0670.0150.0170.0190.0320.0270.0230.0300.0000.0290.0380.0550.0270.0390.0590.0450.0390.0490.1060.0000.0060.0000.0000.0090.0140.0130.0000.0000.0000.0000.0000.0560.0620.0130.0460.0000.0000.0550.0000.0000.0320.0190.0000.0120.0800.0000.0110.0790.0090.0360.0410.0260.0650.1200.0100.0850.0000.053
Generator Bearing Temp. Avg. [°C]0.0000.0260.0260.0090.0050.0000.0070.0000.0000.0000.0000.0000.0000.0000.0000.0630.0270.0340.0200.0240.0330.0000.0270.0220.0270.0071.0000.0630.0640.0320.0450.0350.0160.0080.0120.0120.0160.1040.0010.0080.0000.0000.0000.0060.0070.0000.0130.0070.0120.0060.0070.0000.0000.0120.0000.0070.0020.0070.0090.0080.0170.0220.0200.0590.0630.0640.0000.0030.0000.0100.0000.0000.0000.0000.0000.0250.0160.0270.0890.0060.0000.0130.0010.0100.0030.0170.0000.0240.0120.0330.0000.0300.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0010.0000.0000.0000.0000.0060.0100.0100.0000.0160.0000.0120.0120.0130.0060.0430.0210.0230.0120.0000.0631.0000.0170.0450.0430.0470.0090.0000.0110.0160.0080.0510.0000.0090.0000.0000.0000.0000.0000.0060.0000.0170.0000.0080.0080.0100.0090.0000.0150.0140.0090.0000.0000.0140.0230.0120.0000.0480.0500.0510.0000.0000.0140.0190.0000.0180.0000.0000.0000.0000.0180.0020.0250.0060.0060.0070.0000.0000.0120.0000.0040.0210.0000.0130.0270.0020.000
Generator CoolingWater Temp. Avg. [°C]0.0000.0000.0110.0000.0000.0070.0050.0040.0000.0040.0120.0070.0000.0000.0000.0390.0220.0120.2400.0210.0360.0320.0320.0190.0500.0000.0640.0171.0000.0490.0520.0420.0340.0070.0190.0090.0270.0630.0920.0140.0090.0130.0110.0000.0070.0040.0000.0000.0090.0000.0000.0000.0030.0000.0090.0000.0000.0000.0000.1210.1860.1400.0000.0330.0270.0290.0040.0040.0120.0110.0080.0000.0050.0000.0090.0240.0000.0080.0320.0270.0000.0220.0210.0280.0110.0100.0040.0330.0200.0390.0000.0120.000
Generator Phase1 Temp. Avg. [°C]0.0000.0000.0160.0000.0070.0330.0040.0100.0240.0120.0050.0130.0000.0190.0000.0060.0450.0000.0350.1100.1230.0550.0880.0630.1490.0000.0320.0450.0491.0000.3760.4250.0590.0470.0000.0340.0240.0130.0550.0290.0280.0310.0300.0000.0270.0190.0100.0370.0270.0420.0170.0250.0030.0220.0220.0000.0090.0020.0000.0710.0400.0940.0090.0460.0270.0400.0000.0000.0250.0000.0000.0000.0000.0000.0000.0250.0230.0000.0280.0160.0000.0000.0220.0350.0050.0240.0080.0450.0380.0240.0250.0090.013
Generator Phase2 Temp. Avg. [°C]0.0000.0000.0140.0000.0120.0320.0070.0210.0220.0090.0000.0080.0000.0120.0090.0160.0490.0070.0410.1170.1320.0490.0790.0660.1340.0080.0450.0430.0520.3761.0000.2660.0450.0270.0000.0170.0200.0270.0640.0250.0160.0220.0220.0000.0180.0150.0120.0170.0180.0190.0060.0100.0000.0060.0200.0000.0070.0060.0000.0820.0510.0830.0080.0160.0100.0280.0000.0000.0240.0000.0000.0000.0000.0000.0000.0190.0220.0000.0170.0120.0000.0000.0140.0360.0000.0200.0140.0400.0250.0240.0150.0000.012
Generator Phase3 Temp. Avg. [°C]0.0000.0000.0110.0000.0060.0270.0110.0000.0100.0000.0000.0090.0000.0000.0000.0170.0500.0080.0320.1190.1340.0460.0890.0600.1460.0000.0350.0470.0420.4250.2661.0000.0540.0320.0100.0410.0220.0110.0560.0230.0200.0230.0310.0040.0270.0120.0000.0210.0250.0200.0100.0190.0000.0090.0140.0000.0150.0020.0000.0760.0500.0770.0250.0500.0290.0210.0000.0000.0290.0070.0000.0000.0020.0000.0000.0230.0160.0000.0330.0110.0000.0050.0120.0410.0110.0230.0220.0470.0250.0410.0220.0080.002
Generator RPM Avg. [RPM]0.0000.0000.0300.0310.0860.1240.0650.0710.0380.2650.1170.2520.1800.0060.0320.0100.0140.0150.0090.0930.1490.1100.1890.2060.1080.0560.0160.0090.0340.0590.0450.0541.0000.4230.3780.4700.0360.0090.0000.1800.1460.1410.1480.0000.1550.1710.1500.1660.1540.1630.1050.1600.2570.1460.1430.1460.0120.0140.0050.0200.0280.0380.0080.0120.0120.0160.1090.1040.0260.2800.0060.0000.1070.0190.0210.0250.0440.0000.0180.3410.0590.0850.3290.0100.1220.1630.1790.7460.3910.3460.4170.0000.022
Generator RPM Max. [RPM]0.0000.0000.0240.0430.1360.0830.0720.0470.0520.2360.2830.1620.1510.0000.0440.0110.0110.0260.0000.0310.0820.0310.0780.1200.0350.1370.0080.0000.0070.0470.0270.0320.4231.0000.1830.3380.0250.0060.0000.1240.1110.1120.1130.0000.1160.1620.1530.1760.1150.1610.1100.1440.1750.2620.0890.0830.0090.0140.0010.0090.0180.0230.0160.0200.0000.0120.0610.0620.0680.2250.0090.0120.0650.0030.0250.0000.0400.0060.0190.2220.0000.1510.2120.0340.1280.1200.1000.3510.7670.1530.2930.0170.077
Generator RPM Min. [RPM]0.0000.0000.0060.0180.0760.0800.0540.1010.0240.2850.0860.3760.2660.0050.0330.0050.0030.0000.0100.0400.1110.0620.1740.1810.0380.0370.0120.0110.0190.0000.0000.0100.3780.1831.0000.2670.0410.0100.0100.2480.1260.1260.1340.0120.1260.0950.1800.0990.1520.0950.1710.1090.4000.0990.2610.2270.0000.0000.0150.0280.0400.0340.0030.0250.0340.0290.0890.0860.2080.4620.0000.0100.0920.0000.0110.0930.0410.0090.0080.4140.1860.1810.3970.0130.2730.1580.2750.4070.1630.7440.2290.0000.002
Generator RPM StdDev [RPM]0.0000.0020.0210.0340.0680.0710.0440.0530.0860.2500.0750.2470.4010.0000.0460.0050.0220.0140.0000.0290.0950.0680.1080.1090.0470.0670.0120.0160.0090.0340.0170.0410.4700.3380.2671.0000.0310.0070.0000.2350.1040.1110.1110.0090.1340.1580.2450.2140.1360.1590.1860.2240.2370.1060.1450.2030.0100.0120.0090.0050.0160.0140.0000.0080.0150.0330.0730.0620.0000.2650.0000.0000.0720.0110.0220.0340.1040.0080.0170.2980.0030.1360.2940.0270.2990.1370.1360.4320.2940.2360.6940.0150.051
Generator SlipRing Temp. Avg. [°C]0.0020.0000.1100.0000.0030.0170.0110.0110.0110.0570.0190.0430.0410.0000.0090.0090.0220.0300.0130.0360.0450.0130.0500.0370.0310.0150.0160.0080.0270.0240.0200.0220.0360.0250.0410.0311.0000.0050.0110.0270.0000.0000.0110.0000.0210.0110.0340.0300.0230.0080.0280.0290.0300.0080.0140.0150.0000.0010.0000.0090.0410.0200.0810.0340.0250.0330.0030.0100.0170.0410.0000.0000.0040.0000.0000.0210.0000.0000.1060.0340.0210.0150.0330.0120.0270.0240.0150.0300.0230.0420.0250.0320.007
Grid Busbar Temp. Avg. [°C]0.0000.0000.0390.0110.0050.0030.0000.0000.0040.0000.0000.0130.0080.0220.0430.1300.0140.0170.0040.0130.0320.0000.0220.0100.0070.0170.1040.0510.0630.0130.0270.0110.0090.0060.0100.0070.0051.0000.0080.0050.0140.0000.0060.0020.0000.0040.0120.0090.0000.0000.0080.0000.0140.0030.0000.0000.0040.0000.0000.0160.0090.0220.0150.1170.0600.1240.0000.0000.0000.0210.0000.0000.0000.0000.0000.0200.0060.0090.1210.0220.0060.0000.0250.0290.0150.0000.0020.0170.0000.0120.0110.0400.002
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0250.0010.0000.0220.0240.0100.0110.0130.0000.0000.0050.0240.0000.1330.0420.0380.0180.0270.0140.0200.0190.0010.0000.0920.0550.0640.0560.0000.0000.0100.0000.0110.0081.0000.0220.0670.0660.0620.0000.0420.0210.0230.0300.0570.0420.0280.0380.0090.0230.0120.0110.0000.0090.0000.3220.2150.1860.0090.0240.0230.0190.0250.0270.0020.0000.0000.0000.0250.0000.0000.0000.0100.0130.0080.0150.0300.0170.0160.0050.0180.0620.0000.0000.0000.0110.0000.0000.024
Grid Production CosPhi Avg.0.0000.0000.0000.0220.0690.0410.0350.0640.0230.2490.2030.3240.2710.0000.0330.0130.0310.0090.0070.0260.0650.0150.0970.0950.0110.0320.0080.0090.0140.0290.0250.0230.1800.1240.2480.2350.0270.0050.0221.0000.1740.1930.2000.0000.1780.1750.2080.1850.2480.2200.1780.2360.3940.1340.2630.2300.0000.0180.0000.0210.0420.0450.0000.0090.0080.0150.0580.0550.0230.4120.0000.0000.0570.0000.0050.1880.0760.0130.0210.5360.0190.1940.4900.0740.3010.2520.2490.1950.0970.1930.1940.0270.084
Grid Production CurrentPhase1 Avg. [A]0.0000.0000.0110.0140.0000.1910.1170.0790.0400.1540.1020.1310.1050.0000.0300.0000.0200.0190.0200.0390.0340.0460.0350.0270.0200.0270.0000.0000.0090.0280.0160.0200.1460.1110.1260.1040.0000.0140.0670.1741.0000.8150.7820.0000.5720.2880.2930.2810.6610.3420.3470.3230.2050.1590.1300.1050.0080.0120.0000.0650.0470.0460.0290.0270.0080.0290.1420.1370.0450.1410.0000.0000.1430.0000.0250.1550.0780.0040.0200.2330.1810.3750.2420.0180.0650.6560.1250.1470.0880.0970.0970.0180.069
Grid Production CurrentPhase2 Avg. [A]0.0000.0000.0110.0170.0000.1850.1210.0830.0450.1560.1010.1380.1100.0000.0360.0060.0240.0240.0150.0420.0340.0410.0410.0280.0180.0230.0000.0000.0130.0310.0220.0230.1410.1120.1260.1110.0000.0000.0660.1930.8151.0000.7960.0000.5690.2880.2860.2880.6680.3520.3530.3350.2280.1700.1460.1130.0110.0170.0000.0560.0480.0400.0270.0250.0050.0270.1430.1380.0410.1430.0110.0000.1440.0110.0390.1440.0770.0100.0220.2370.1710.3720.2690.0210.0640.6560.1410.1400.0890.0930.1000.0170.070
Grid Production CurrentPhase3 Avg. [A]0.0000.0000.0050.0220.0000.1890.1110.0830.0470.1730.1120.1510.1230.0000.0240.0030.0220.0280.0260.0390.0340.0430.0450.0310.0210.0300.0000.0000.0110.0300.0220.0310.1480.1130.1340.1110.0110.0060.0620.2000.7820.7961.0000.0000.5840.3050.2980.3050.6960.3680.3550.3480.2340.1790.1440.1140.0090.0170.0000.0600.0490.0450.0280.0190.0000.0220.1400.1350.0470.1660.0000.0000.1420.0000.0250.1230.0790.0000.0180.2610.1760.3960.2770.0200.0750.6900.1460.1470.0880.1020.1040.0090.080
Grid Production Frequency Avg. [Hz]0.0000.0000.0000.0000.0000.0000.0000.0050.0070.0000.0000.0120.0000.0000.0000.0000.0000.0030.0000.0050.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0040.0000.0000.0120.0090.0000.0020.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0090.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0050.0000.0090.0000.0050.0000.0000.0120.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0000.0000.0000.0000.0140.2130.1230.0720.0280.2060.1540.1690.1750.0000.0150.0050.0100.0250.0190.0650.0460.0410.0650.0570.0300.0290.0070.0000.0070.0270.0180.0270.1550.1160.1260.1340.0210.0000.0420.1780.5720.5690.5840.0001.0000.3920.4150.4060.6980.3390.3210.3820.1400.1680.0700.0850.0010.0190.0080.0410.0470.0300.0000.0190.0100.0200.0800.0880.0370.2020.0060.0000.0790.0160.0050.1340.0810.0130.0140.1950.2560.4380.1760.0020.0990.6860.0930.1510.1050.1030.1320.0030.096
Grid Production PossiblePower Max. [W]0.0000.0000.0000.0000.0000.0880.1220.0430.0320.2090.1780.1520.1720.0000.0000.0030.0120.0400.0000.0650.0440.0570.0790.0650.0350.0380.0000.0060.0040.0190.0150.0120.1710.1620.0950.1580.0110.0040.0210.1750.2880.2880.3050.0000.3921.0000.2950.3940.3410.7190.2080.3440.1390.1820.0700.1190.0000.0130.0000.0110.0230.0200.0000.0080.0000.0140.1210.1220.0480.2030.0030.0000.1200.0130.0130.0460.0670.0380.0090.2010.0830.2780.1740.0440.1100.3470.1200.1760.1410.0760.1760.0020.097
Grid Production PossiblePower Min. [W]0.0000.0000.0080.0000.0000.0950.0620.1070.0300.2400.1320.2030.2890.0000.0170.0100.0140.0210.0000.0250.0400.0200.0610.0730.0070.0550.0130.0000.0000.0100.0120.0000.1500.1530.1800.2450.0340.0120.0230.2080.2930.2860.2980.0000.4150.2951.0000.3080.3460.2770.5700.3180.1700.1360.0860.1440.0090.0110.0130.0160.0320.0250.0000.0370.0190.0250.0490.0520.0620.2440.0000.0000.0490.0000.0000.0890.0910.0070.0240.2050.0950.3310.1850.0000.2630.3490.1040.1590.1300.1470.2170.0110.105
Grid Production PossiblePower StdDev [W]0.0000.0000.0000.0030.0130.0600.0920.0590.1160.2650.1880.1980.2320.0000.0130.0000.0000.0220.0130.0350.0270.0250.0560.0530.0170.0270.0070.0170.0000.0370.0170.0210.1660.1760.0990.2140.0300.0090.0300.1850.2810.2880.3050.0000.4060.3940.3081.0000.3610.3590.2360.7800.1740.1950.1050.1300.0000.0100.0000.0280.0350.0310.0000.0100.0120.0210.0650.0670.0520.2480.0040.0000.0640.0140.0130.0630.1000.0000.0200.2160.0940.3290.1900.0300.1390.3670.1220.1660.1570.0840.1830.0120.113
Grid Production Power Avg. [W]0.0000.0000.0000.0000.0030.2090.1170.0770.0360.2070.1360.1830.1630.0000.0280.0000.0170.0250.0230.0530.0420.0500.0530.0440.0250.0390.0120.0000.0090.0270.0180.0250.1540.1150.1520.1360.0230.0000.0570.2480.6610.6680.6960.0000.6980.3410.3460.3611.0000.3870.3870.4190.2210.1870.1210.1020.0000.0130.0000.0480.0550.0410.0090.0280.0210.0310.1520.1460.0490.2020.0000.0000.1500.0000.0200.1290.0930.0110.0190.3090.2550.4660.2640.0000.1060.8800.1500.1570.0980.1210.1300.0180.119
Grid Production Power Max. [W]0.0000.0000.0000.0100.0000.0840.1150.0510.0330.1980.1650.1540.1540.0000.0230.0000.0170.0380.0040.0510.0340.0590.0640.0460.0260.0590.0060.0080.0000.0420.0190.0200.1630.1610.0950.1590.0080.0000.0420.2200.3420.3520.3680.0000.3390.7190.2770.3590.3871.0000.2540.3750.1790.2470.0910.1090.0000.0050.0000.0230.0320.0270.0050.0220.0000.0180.0980.0890.0150.2100.0000.0000.0970.0000.0230.0420.0660.0240.0190.2380.0530.2890.2330.0000.1060.3920.1340.1730.1330.0720.1760.0180.096
Grid Production Power Min. [W]0.0000.0000.0070.0000.0090.0810.0680.1130.0380.1890.0870.1720.2110.0000.0190.0100.0100.0260.0140.0070.0170.0260.0320.0290.0090.0450.0070.0080.0000.0170.0060.0100.1050.1100.1710.1860.0280.0080.0280.1780.3470.3530.3550.0000.3210.2080.5700.2360.3870.2541.0000.2890.1760.1060.1780.1210.0130.0140.0120.0210.0400.0300.0000.0210.0210.0250.0530.0390.0590.1740.0090.0000.0520.0000.0220.1030.1170.0130.0110.1870.0830.3260.1790.0040.2090.3850.1010.1120.0830.1320.1730.0000.091
Grid Production Power StdDev [W]0.0000.0000.0000.0000.0180.0510.0960.0600.1120.2500.1430.2100.2470.0000.0180.0000.0040.0200.0130.0300.0250.0220.0500.0470.0130.0390.0000.0100.0000.0250.0100.0190.1600.1440.1090.2240.0290.0000.0380.2360.3230.3350.3480.0000.3820.3440.3180.7800.4190.3750.2891.0000.2140.1850.1360.1590.0000.0070.0000.0270.0410.0320.0000.0130.0180.0190.1030.0820.0730.2460.0110.0000.1010.0230.0610.0630.0910.0000.0110.2560.1120.3260.2110.0510.1600.4270.1430.1620.1270.0860.1930.0210.104
Grid Production ReactivePower Avg. [W]0.0070.0000.0000.0350.0930.0460.0440.0940.0320.4410.1650.6730.4940.0000.0320.0180.0130.0000.0000.0030.0760.0000.1010.1380.0000.0490.0000.0090.0030.0030.0000.0000.2570.1750.4000.2370.0300.0140.0090.3940.2050.2280.2340.0110.1400.1390.1700.1740.2210.1790.1760.2141.0000.1750.6000.4840.0000.0070.0000.0170.0160.0180.0000.0240.0320.0340.1220.1100.3100.6950.0000.0000.1230.0000.0390.1190.0730.0060.0230.6660.1570.3000.7340.1670.5280.2160.6680.2760.1450.3070.2010.0210.040
Grid Production ReactivePower Max. [W]0.0000.0000.0070.0360.1120.0370.0520.0170.0370.1970.2940.1180.0960.0000.0240.0000.0250.0190.0000.0080.0250.0130.0580.0620.0000.1060.0120.0000.0000.0220.0060.0090.1460.2620.0990.1060.0080.0030.0230.1340.1590.1700.1790.0000.1680.1820.1360.1950.1870.2470.1060.1850.1751.0000.1350.0790.0090.0160.0000.0190.0200.0080.0000.0170.0000.0090.0590.0530.0000.1930.0000.0090.0580.0000.0200.0190.1470.0000.0130.2200.0170.1460.2310.0100.0440.1840.1410.1560.2300.0880.0920.0000.087
Grid Production ReactivePower Min. [W]0.0020.0000.0000.0000.0340.0380.0260.0800.0380.2490.0700.4690.3330.0000.0150.0240.0000.0000.0000.0080.0630.0170.0750.0860.0160.0000.0000.0150.0090.0220.0200.0140.1430.0890.2610.1450.0140.0000.0120.2630.1300.1460.1440.0000.0700.0700.0860.1050.1210.0910.1780.1360.6000.1351.0000.4180.0000.0150.0090.0140.0180.0250.0000.0140.0230.0220.0540.0440.2310.4320.0000.0000.0540.0000.0240.1110.1740.0100.0200.3820.1140.1910.4050.1310.3510.1160.4110.1510.0760.2170.1120.0000.021
Grid Production ReactivePower StdDev [W]0.0000.0000.0000.0000.0150.0510.0330.0690.0180.2380.0550.3870.3510.0050.0110.0030.0220.0130.0000.0000.0450.0290.0900.1200.0130.0060.0070.0140.0000.0000.0000.0000.1460.0830.2270.2030.0150.0000.0110.2300.1050.1130.1140.0000.0850.1190.1440.1300.1020.1090.1210.1590.4840.0790.4181.0000.0000.0100.0060.0090.0060.0120.0000.0200.0180.0280.0490.0340.2010.3970.0000.0000.0480.0000.0240.0230.1170.0000.0050.3330.1150.1740.3310.1730.3590.1060.3800.1480.0800.1610.1690.0040.009
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0000.0000.0050.0010.0000.0020.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0060.0070.0040.0030.0060.0000.0020.0090.0000.0090.0070.0150.0120.0090.0000.0100.0000.0040.0000.0000.0080.0110.0090.0000.0010.0000.0090.0000.0000.0000.0130.0000.0000.0090.0000.0001.0000.5190.5140.0170.0000.0010.0080.0000.0070.0180.0000.0000.0000.0000.0990.0000.0000.0280.0160.0000.0000.0000.0000.0000.0000.0100.0000.0000.0000.0000.0000.0080.0060.0000.0100.0000.000
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0030.0000.0000.0000.0000.0060.0000.0050.0160.0080.0090.0000.0000.0000.0000.0060.0080.0000.0000.0000.0000.0000.0000.0000.0070.0000.0000.0020.0060.0020.0140.0140.0000.0120.0010.0000.0090.0180.0120.0170.0170.0000.0190.0130.0110.0100.0130.0050.0140.0070.0070.0160.0150.0100.5191.0000.3740.0080.0000.0000.0040.0050.0010.0120.0000.0000.0030.0130.0880.0000.0000.0060.0000.0000.0000.0000.0000.0130.0080.0110.0190.0000.0060.0080.0060.0160.0080.0000.0110.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0000.0000.0000.0000.0080.0000.0000.0000.0040.0060.0000.0000.0000.0000.0000.0000.0030.0080.0000.0020.0120.0000.0000.0140.0090.0090.0000.0000.0000.0000.0000.0050.0010.0150.0090.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0130.0000.0000.0000.0120.0000.0000.0000.0090.0060.5140.3741.0000.0200.0040.0000.0000.0000.0060.0150.0000.0000.0300.0100.0710.0000.0000.0000.0000.0000.0000.0000.0050.0060.0320.0060.0000.0000.0000.0000.0010.0140.0060.0120.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0000.0170.0000.0000.0360.0310.0100.0190.0340.0000.0260.0150.0000.0030.0000.0380.0000.1640.0580.0500.0410.0180.0260.0550.0140.0080.0140.1210.0710.0820.0760.0200.0090.0280.0050.0090.0160.3220.0210.0650.0560.0600.0000.0410.0110.0160.0280.0480.0230.0210.0270.0170.0190.0140.0090.0170.0080.0201.0000.3180.3080.0120.0000.0100.0140.0240.0260.0130.0100.0000.0000.0240.0000.0000.0130.0060.0040.0000.0200.0250.0270.0210.0200.0030.0570.0000.0230.0120.0370.0000.0110.011
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0000.0120.0000.0180.0050.0000.0000.0300.0120.0360.0270.0000.0030.0060.0120.0060.2410.0340.0410.0290.0370.0260.0350.0130.0170.0230.1860.0400.0510.0500.0280.0180.0400.0160.0410.0090.2150.0420.0470.0480.0490.0000.0470.0230.0320.0350.0550.0320.0400.0410.0160.0200.0180.0060.0000.0000.0040.3181.0000.2890.0000.0140.0000.0000.0160.0130.0000.0230.0040.0000.0150.0000.0000.0310.0120.0050.0220.0370.0060.0340.0290.0280.0000.0620.0030.0290.0120.0360.0070.0000.019
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0290.0160.0050.0130.0320.0020.0290.0260.0150.0130.0000.0210.0000.2250.0580.0510.0380.0290.0200.0530.0000.0220.0120.1400.0940.0830.0770.0380.0230.0340.0140.0200.0220.1860.0450.0460.0400.0450.0000.0300.0200.0250.0310.0410.0270.0300.0320.0180.0080.0250.0120.0010.0000.0000.3080.2891.0000.0090.0250.0200.0310.0360.0260.0000.0130.0000.0000.0350.0000.0000.0150.0180.0000.0120.0390.0140.0150.0310.0240.0000.0460.0000.0350.0250.0540.0090.0000.007
HVTrafo AirOutlet Temp. Avg. [°C]0.0000.0000.0540.0140.0000.0060.0080.0000.0090.0000.0030.0090.0000.0000.0000.0080.0210.0370.0030.0100.0180.0000.0000.0000.0000.0000.0200.0000.0000.0090.0080.0250.0080.0160.0030.0000.0810.0150.0090.0000.0290.0270.0280.0080.0000.0000.0000.0000.0090.0050.0000.0000.0000.0000.0000.0000.0080.0040.0000.0120.0000.0091.0000.0260.0150.0170.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0180.0100.0810.0000.0000.0070.0000.0030.0080.0000.0000.0050.0000.0000.0000.0120.000
HVTrafo Phase1 Temp. Avg. [°C]0.0120.0000.0380.0110.0000.0000.0130.0000.0090.0150.0000.0200.0260.0050.0210.0430.0280.0000.0000.0030.0290.0000.0190.0100.0100.0000.0590.0480.0330.0460.0160.0500.0120.0200.0250.0080.0340.1170.0240.0090.0270.0250.0190.0000.0190.0080.0370.0100.0280.0220.0210.0130.0240.0170.0140.0200.0000.0050.0000.0000.0140.0250.0261.0000.1770.2970.0000.0080.0380.0410.0100.0340.0060.0000.0100.0120.0150.0000.0480.0200.0420.0220.0240.0160.0240.0240.0070.0140.0090.0200.0210.0260.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0160.0200.0000.0000.0000.0100.0030.0120.0230.0000.0290.0300.0050.0110.0500.0080.0000.0000.0000.0230.0000.0040.0000.0000.0000.0630.0500.0270.0270.0100.0290.0120.0000.0340.0150.0250.0600.0230.0080.0080.0050.0000.0000.0100.0000.0190.0120.0210.0000.0210.0180.0320.0000.0230.0180.0070.0010.0060.0100.0000.0200.0150.1771.0000.2140.0000.0000.0500.0550.0000.0000.0000.0000.0000.0090.0120.0000.0280.0240.0610.0200.0170.0000.0410.0170.0200.0110.0040.0280.0170.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0330.0150.0040.0100.0000.0000.0070.0200.0000.0250.0360.0100.0360.0780.0230.0000.0070.0000.0330.0050.0190.0160.0090.0000.0640.0510.0290.0400.0280.0210.0160.0120.0290.0330.0330.1240.0190.0150.0290.0270.0220.0000.0200.0140.0250.0210.0310.0180.0250.0190.0340.0090.0220.0280.0180.0120.0150.0140.0000.0310.0170.2970.2141.0000.0000.0000.0200.0420.0170.0000.0000.0100.0000.0090.0200.0000.0690.0300.0250.0210.0350.0190.0300.0220.0130.0150.0000.0130.0340.0210.000
HourCounters Average AlarmActive Avg. [h]0.0000.0000.0060.0000.0410.0000.0000.0000.0000.1450.0590.1140.0910.0000.0240.0000.0000.0000.0000.0050.0140.0280.0210.0270.0000.0560.0000.0000.0040.0000.0000.0000.1090.0610.0890.0730.0030.0000.0250.0580.1420.1430.1400.0000.0800.1210.0490.0650.1520.0980.0530.1030.1220.0590.0540.0490.0000.0000.0000.0240.0160.0360.0000.0000.0000.0001.0000.8800.1860.0000.1380.0260.9710.2090.3080.0830.0260.0090.0070.1540.1840.0050.1430.0560.0040.1540.0780.1130.0540.0710.0640.0480.000
HourCounters Average AmbientOk Avg. [h]0.0000.0000.0000.0000.0390.0000.0000.0000.0000.1310.0550.1020.0820.0000.0220.0000.0010.0000.0000.0000.0150.0300.0200.0190.0000.0620.0030.0000.0040.0000.0000.0000.1040.0620.0860.0620.0100.0000.0270.0550.1370.1380.1350.0000.0880.1220.0520.0670.1460.0890.0390.0820.1100.0530.0440.0340.0000.0000.0000.0260.0130.0260.0000.0080.0000.0000.8801.0000.1920.0000.2740.1380.9060.2940.2410.0940.0310.0000.0010.1390.1900.0000.1290.0570.0000.1550.0710.1080.0530.0680.0520.0500.000
HourCounters Average Gen1 Avg. [h]0.0000.0000.0000.0000.0000.0290.0270.0550.0050.1490.0320.2830.2220.0000.0290.0050.0230.0000.0000.0180.0000.0090.0000.0300.0170.0130.0000.0140.0120.0250.0240.0290.0260.0680.2080.0000.0170.0000.0020.0230.0450.0410.0470.0090.0370.0480.0620.0520.0490.0150.0590.0730.3100.0000.2310.2010.0000.0030.0300.0130.0000.0000.0000.0380.0500.0200.1860.1921.0000.5220.0420.0240.1910.0410.0490.0070.0140.0110.0000.0190.5880.4010.0070.2290.2030.0570.2130.0380.0480.1700.0130.0150.011
HourCounters Average Gen2 Avg. [h]0.0000.0000.0020.0290.0920.0610.0480.0680.0220.4380.2050.5700.4420.0000.0470.0180.0060.0000.0000.0000.0860.0000.1140.1610.0060.0460.0100.0190.0110.0000.0000.0070.2800.2250.4620.2650.0410.0210.0000.4120.1410.1430.1660.0120.2020.2030.2440.2480.2020.2100.1740.2460.6950.1930.4320.3970.0000.0130.0100.0100.0230.0130.0080.0410.0550.0420.0000.0000.5221.0000.0000.0120.0060.0000.0090.1110.0740.0000.0170.6670.2640.5040.6250.0690.5000.2100.4740.3000.1890.3640.2250.0080.072
HourCounters Average GridOk Avg. [h]0.0000.0000.0240.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0060.0090.0000.0000.0000.0000.0000.0000.0000.0110.0000.0000.0060.0030.0000.0040.0000.0000.0090.0110.0000.0000.0000.0000.0990.0880.0710.0000.0040.0000.0000.0100.0000.0170.1380.2740.0420.0001.0000.2940.2120.6250.5130.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0040.0000.0000.0000.000
HourCounters Average GridOn Avg. [h]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0180.0000.0000.0000.0000.0000.0120.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0340.0000.0000.0260.1380.0240.0120.2941.0000.1330.0000.2870.0150.0000.0000.0000.0000.0000.0180.0000.0000.0000.0220.0030.0110.0090.0060.0000.0000.000
HourCounters Average Run Avg. [h]0.0000.0000.0080.0000.0410.0000.0000.0000.0000.1450.0580.1150.0910.0000.0270.0000.0000.0000.0000.0040.0130.0270.0210.0260.0000.0550.0000.0000.0050.0000.0000.0020.1070.0650.0920.0720.0040.0000.0250.0570.1430.1440.1420.0000.0790.1200.0490.0640.1500.0970.0520.1010.1230.0580.0540.0480.0000.0000.0000.0240.0150.0350.0000.0060.0000.0000.9710.9060.1910.0060.2120.1331.0000.2070.3780.0870.0260.0090.0020.1550.1810.0000.1440.0550.0070.1590.0800.1110.0580.0730.0600.0470.000
HourCounters Average ServiceOn Avg. [h]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0000.0000.0000.0060.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0190.0030.0000.0110.0000.0000.0000.0000.0000.0110.0000.0000.0160.0130.0000.0140.0000.0000.0000.0230.0000.0000.0000.0000.0280.0060.0000.0000.0000.0000.0000.0000.0000.0100.2090.2940.0410.0000.6250.0000.2071.0000.5270.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.000
HourCounters Average TurbineOk Avg. [h]0.0000.0000.0190.0000.0000.0000.0000.0000.0000.0380.0000.0380.0260.0000.0000.0000.0000.0180.0000.0000.0000.0000.0020.0000.0000.0000.0000.0000.0090.0000.0000.0000.0210.0250.0110.0220.0000.0000.0000.0050.0250.0390.0250.0000.0050.0130.0000.0130.0200.0230.0220.0610.0390.0200.0240.0240.0160.0000.0000.0000.0000.0000.0000.0100.0000.0000.3080.2410.0490.0090.5130.2870.3780.5271.0000.0000.0000.0000.0050.0320.0000.0000.0420.0000.0000.0290.0240.0180.0240.0060.0170.0000.000
HourCounters Average WindOk Avg. [h]0.0000.0000.0000.0020.0150.0220.0460.0560.0070.0630.1540.1060.0570.0000.0000.0190.0000.0050.0000.0220.0280.0080.0000.0040.0010.0320.0250.0000.0240.0250.0190.0230.0250.0000.0930.0340.0210.0200.0000.1880.1550.1440.1230.0000.1340.0460.0890.0630.1290.0420.1030.0630.1190.0190.1110.0230.0000.0000.0000.0130.0310.0150.0000.0120.0090.0090.0830.0940.0070.1110.0000.0150.0870.0000.0001.0000.0430.0090.0220.1660.0000.1240.1540.0660.0910.1400.0500.0210.0040.1040.0000.0400.006
HourCounters Average Yaw Avg. [h]0.0040.0000.0000.0120.0050.0070.0210.0080.0540.0870.0260.0520.1050.0000.0000.0200.0000.0000.0040.0120.0290.0230.0150.0240.0080.0190.0160.0180.0000.0230.0220.0160.0440.0400.0410.1040.0000.0060.0100.0760.0780.0770.0790.0000.0810.0670.0910.1000.0930.0660.1170.0910.0730.1470.1740.1170.0000.0000.0000.0060.0120.0180.0180.0150.0120.0200.0260.0310.0140.0740.0000.0000.0260.0000.0000.0431.0000.0000.0110.0890.0120.0850.0890.0300.0810.0930.0380.0480.0410.0390.0870.0090.036
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0110.0000.0000.0000.0000.0100.0160.0000.0090.0000.0000.0160.0000.0090.0040.0160.0120.0300.0000.0000.0150.0000.0000.0000.0270.0020.0080.0000.0000.0000.0000.0060.0090.0080.0000.0090.0130.0130.0040.0100.0000.0000.0130.0380.0070.0000.0110.0240.0130.0000.0060.0000.0100.0000.0000.0000.0000.0040.0050.0000.0100.0000.0000.0000.0090.0000.0110.0000.0000.0000.0090.0000.0000.0090.0001.0000.0200.0000.0160.0150.0000.0280.0080.0110.0140.0110.0060.0180.0230.0140.000
Nacelle Temp. Avg. [°C]0.0000.0000.1140.0090.0060.0190.0000.0000.0010.0260.0140.0070.0170.0120.0180.1150.0150.0520.0120.0180.0260.0020.0130.0060.0000.0120.0890.0250.0320.0280.0170.0330.0180.0190.0080.0170.1060.1210.0080.0210.0200.0220.0180.0000.0140.0090.0240.0200.0190.0190.0110.0110.0230.0130.0200.0050.0000.0000.0050.0000.0220.0120.0810.0480.0280.0690.0070.0010.0000.0170.0000.0000.0020.0000.0050.0220.0110.0201.0000.0170.0000.0200.0280.0190.0000.0170.0000.0210.0000.0050.0140.0690.009
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0000.0000.0360.1280.0550.0370.0510.0240.4130.2600.4770.3480.0000.0420.0140.0330.0040.0080.0200.1150.0150.1370.1660.0230.0800.0060.0060.0270.0160.0120.0110.3410.2220.4140.2980.0340.0220.0150.5360.2330.2370.2610.0030.1950.2010.2050.2160.3090.2380.1870.2560.6660.2200.3820.3330.0000.0130.0060.0200.0370.0390.0000.0200.0240.0300.1540.1390.0190.6670.0000.0000.1550.0000.0320.1660.0890.0000.0171.0000.0120.1960.8440.0560.4060.3530.4580.3590.1960.3210.2660.0270.072
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0000.0000.0000.0030.1020.0520.0490.0000.0660.0190.1600.1270.0000.0070.0000.0170.0000.0000.0350.0450.0240.0470.0290.0100.0000.0000.0060.0000.0000.0000.0000.0590.0000.1860.0030.0210.0060.0300.0190.1810.1710.1760.0000.2560.0830.0950.0940.2550.0530.0830.1120.1570.0170.1140.1150.0000.0080.0320.0250.0060.0140.0000.0420.0610.0250.1840.1900.5880.2640.0000.0000.1810.0000.0000.0000.0120.0160.0000.0121.0000.0320.0000.1530.0840.2860.1190.0560.0000.1560.0160.0110.008
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0000.0090.0010.0060.0930.0640.0740.0340.2680.1190.2930.2720.0000.0340.0000.0000.0210.0080.0000.0140.0160.0000.0360.0000.0110.0130.0070.0220.0000.0000.0050.0850.1510.1810.1360.0150.0000.0170.1940.3750.3720.3960.0000.4380.2780.3310.3290.4660.2890.3260.3260.3000.1460.1910.1740.0100.0110.0060.0270.0340.0150.0070.0220.0200.0210.0050.0000.4010.5040.0000.0180.0000.0000.0000.1240.0850.0150.0200.1960.0321.0000.1720.0710.2730.4900.1910.0970.1180.1450.1050.0050.124
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0090.0000.0000.0440.1300.0530.0430.0500.0250.3890.2430.4510.3340.0000.0430.0160.0330.0060.0000.0130.1070.0140.1320.1580.0200.0790.0010.0000.0210.0220.0140.0120.3290.2120.3970.2940.0330.0250.0160.4900.2420.2690.2770.0050.1760.1740.1850.1900.2640.2330.1790.2110.7340.2310.4050.3310.0000.0190.0000.0210.0290.0310.0000.0240.0170.0350.1430.1290.0070.6250.0000.0000.1440.0000.0420.1540.0890.0000.0280.8440.0000.1721.0000.0610.3870.2550.5410.3450.1830.3090.2590.0190.054
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0000.0000.0140.0240.0000.0160.0220.0160.0950.0350.1660.1350.0050.0160.0270.0050.0130.0000.0000.0270.0240.0000.0310.0000.0090.0100.0000.0280.0350.0360.0410.0100.0340.0130.0270.0120.0290.0050.0740.0180.0210.0200.0000.0020.0440.0000.0300.0000.0000.0040.0510.1670.0100.1310.1730.0000.0000.0000.0200.0280.0240.0030.0160.0000.0190.0560.0570.2290.0690.0000.0000.0550.0000.0000.0660.0300.0280.0190.0560.1530.0710.0611.0000.0670.0000.6880.0110.0190.0100.0060.0240.023
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0000.0000.0120.0390.0080.0100.0600.0240.2550.0670.4480.4880.0000.0180.0000.0180.0000.0130.0200.0380.0180.0420.0690.0120.0360.0030.0120.0110.0050.0000.0110.1220.1280.2730.2990.0270.0150.0180.3010.0650.0640.0750.0090.0990.1100.2630.1390.1060.1060.2090.1600.5280.0440.3510.3590.0000.0060.0000.0030.0000.0000.0080.0240.0410.0300.0040.0000.2030.5000.0000.0000.0070.0000.0000.0910.0810.0080.0000.4060.0840.2730.3870.0671.0000.1090.4220.1390.1020.1960.2460.0160.047
Production LatestAverage Total Active Power Avg. [W]0.0000.0000.0000.0000.0070.2050.1120.0780.0350.2160.1420.1960.1710.0000.0310.0000.0120.0260.0280.0560.0450.0470.0560.0450.0280.0410.0170.0000.0100.0240.0200.0230.1630.1200.1580.1370.0240.0000.0620.2520.6560.6560.6900.0000.6860.3470.3490.3670.8800.3920.3850.4270.2160.1840.1160.1060.0000.0080.0000.0570.0620.0460.0000.0240.0170.0220.1540.1550.0570.2100.0030.0220.1590.0000.0290.1400.0930.0110.0170.3530.2860.4900.2550.0000.1091.0000.1480.1660.0990.1290.1310.0170.121
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0000.0130.0480.0290.0350.0670.0000.3190.1080.4650.3310.0070.0090.0070.0090.0140.0000.0000.0440.0240.0910.1270.0080.0260.0000.0040.0040.0080.0140.0220.1790.1000.2750.1360.0150.0020.0000.2490.1250.1410.1460.0050.0930.1200.1040.1220.1500.1340.1010.1430.6680.1410.4110.3800.0000.0060.0010.0000.0030.0000.0000.0070.0200.0130.0780.0710.2130.4740.0000.0030.0800.0000.0240.0500.0380.0140.0000.4580.1190.1910.5410.6880.4220.1481.0000.1910.0930.1970.1290.0000.009
Rotor RPM Avg. [RPM]0.0000.0000.0200.0350.0890.1100.0480.0700.0250.2820.1170.2600.1930.0110.0300.0130.0130.0080.0150.0730.1480.1150.1920.2240.1020.0650.0240.0210.0330.0450.0400.0470.7460.3510.4070.4320.0300.0170.0000.1950.1470.1400.1470.0000.1510.1760.1590.1660.1570.1730.1120.1620.2760.1560.1510.1480.0080.0160.0140.0230.0290.0350.0050.0140.0110.0150.1130.1080.0380.3000.0000.0110.1110.0000.0180.0210.0480.0110.0210.3590.0560.0970.3450.0110.1390.1660.1911.0000.3160.3680.4000.0000.028
Rotor RPM Max. [RPM]0.0000.0000.0220.0330.1110.0730.0660.0360.0420.2110.2380.1420.1270.0010.0320.0000.0060.0190.0090.0470.0670.0660.0840.1090.0520.1200.0120.0000.0200.0380.0250.0250.3910.7670.1630.2940.0230.0000.0000.0970.0880.0890.0880.0000.1050.1410.1300.1570.0980.1330.0830.1270.1450.2300.0760.0800.0060.0080.0060.0120.0120.0250.0000.0090.0040.0000.0540.0530.0480.1890.0040.0090.0580.0000.0240.0040.0410.0060.0000.1960.0000.1180.1830.0190.1020.0990.0930.3161.0000.1410.2500.0120.062
Rotor RPM Min. [RPM]0.0000.0000.0060.0110.0610.0690.0380.0850.0160.2270.0710.3060.2040.0010.0220.0110.0000.0000.0140.0530.1160.0560.1470.1530.0540.0100.0330.0130.0390.0240.0240.0410.3460.1530.7440.2360.0420.0120.0110.1930.0970.0930.1020.0120.1030.0760.1470.0840.1210.0720.1320.0860.3070.0880.2170.1610.0000.0000.0120.0370.0360.0540.0000.0200.0280.0130.0710.0680.1700.3640.0000.0060.0730.0000.0060.1040.0390.0180.0050.3210.1560.1450.3090.0100.1960.1290.1970.3680.1411.0000.1900.0000.000
Rotor RPM StdDev [RPM]0.0000.0100.0200.0360.0640.0600.0420.0470.0660.2110.0850.2110.3340.0000.0350.0000.0290.0290.0040.0430.1020.0520.0980.0970.0450.0850.0000.0270.0000.0250.0150.0220.4170.2930.2290.6940.0250.0110.0000.1940.0970.1000.1040.0000.1320.1760.2170.1830.1300.1760.1730.1930.2010.0920.1120.1690.0100.0110.0000.0000.0070.0090.0000.0210.0170.0340.0640.0520.0130.2250.0000.0000.0600.0080.0170.0000.0870.0230.0140.2660.0160.1050.2590.0060.2460.1310.1290.4000.2500.1901.0000.0000.044
Spinner Temp. Avg. [°C]0.0000.0000.0570.0010.0200.0000.0000.0000.0000.0130.0210.0200.0060.0150.0890.0360.0000.0110.0000.0000.0060.0000.0050.0150.0000.0000.0300.0020.0120.0090.0000.0080.0000.0170.0000.0150.0320.0400.0000.0270.0180.0170.0090.0000.0030.0020.0110.0120.0180.0180.0000.0210.0210.0000.0000.0040.0000.0000.0000.0110.0000.0000.0120.0260.0000.0210.0480.0500.0150.0080.0000.0000.0470.0000.0000.0400.0090.0140.0690.0270.0110.0050.0190.0240.0160.0170.0000.0000.0120.0000.0001.0000.005
Total Active power [W]0.0000.0000.0010.0000.0120.0000.0110.0100.0080.0710.0870.0530.0650.0000.0090.0000.0110.0240.0100.0010.0000.0000.0110.0000.0070.0530.0000.0000.0000.0130.0120.0020.0220.0770.0020.0510.0070.0020.0240.0840.0690.0700.0800.0000.0960.0970.1050.1130.1190.0960.0910.1040.0400.0870.0210.0090.0000.0000.0000.0110.0190.0070.0000.0000.0000.0000.0000.0000.0110.0720.0000.0000.0000.0000.0000.0060.0360.0000.0090.0720.0080.1240.0540.0230.0470.1210.0090.0280.0620.0000.0440.0051.000

Missing values

2025-05-14T19:28:01.561978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T19:28:02.284062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
02020-01-01 00:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
12020-01-01 00:10:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
22020-01-01 00:20:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
32020-01-01 00:30:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
42020-01-01 00:40:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
52020-01-01 00:50:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
62020-01-01 01:00:0000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
72020-01-01 01:10:0000000100000000000000001000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
82020-01-01 01:20:0000000001100000000000001000000000000001000000000000000100000000000000000000000000000000001000000010000000000000000000000000000000
92020-01-01 01:30:0000110001100000000000001100100010010000000000000000000110000000000000000000000000000010001000000010000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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